Data sharing and transparency are becoming more common across the social sciences. In this article, we provide an overview of ethical, methodological, and technological considerations and challenges when developing large video-based datasets intended to be shared across researchers. We cover data security, storage, and access as well as data documentation, tagging, and transcription. Our discussions

Many studies have compared individual measures of health expectancy across older populations by time-invariant characteristics. However, very few have included time-varying variables when calculating health expectancy. Even among older adults, socioeconomic and demographic characteristics are likely to change over the life course, and these changes may have substantial implications for health outcomes

Sociologists are discussing the need for more formal ways to extract meaning from digital text archives. We focus attention on the seeded topic model, a semi-supervised extension to the standard topic model that allows sociological knowledge to be infused into the computational learning of meaning structures. Seed words help crystallize topics around known concepts, while utilizing topic models’ functionality

This primer systematizes the emerging literature on causal inference using deep neural networks under the potential outcomes framework. It provides an intuitive introduction to building and optimizing custom deep learning models and shows how to adapt them to estimate/predict heterogeneous treatment effects. It also discusses ongoing work to extend causal inference to settings where confounding is

Researchers have developed many uses for digital trace data, yet most online survey experiments continue to rely on attitudinal rather than behavioral measures. We argue that researchers can collect digital trace data during online survey experiments with relative ease, at modest costs, and to substantial benefit. Because digital trace data unobtrusively measure survey participants’ behaviors, they

Instrumental variables (IV) analysis is a powerful, but fragile, tool for drawing causal inferences from observational data. Sociologists increasingly turn to this strategy in settings where unmeasured confounding between the treatment and outcome is likely. This paper reviews the assumptions required for IV and the consequences of violating them, focusing on sociological applications. We highlight

This article uses the example of voter turnout in US presidential elections to compare two new methods for age, period, and cohort (APC) analysis: the APC interaction model and the APC bounding analysis. While discussing the formal, conceptual, and interpretive differences between the two methods, the analysis demonstrates how both methods can be used to generate distinct but complementary findings

Causal decomposition analysis aims to identify risk factors (referred to as “mediators”) that contribute to social disparities in an outcome. Despite promising developments in causal decomposition analysis, current methods are limited to addressing a time-fixed mediator and outcome only, which has restricted our understanding of the causal mechanisms underlying social disparities. In particular, existing

Trust is a foundational concept of contemporary sociological theory. Still, empirical research on trust relies on a relatively small set of measures. These are increasingly debated, potentially undermining large swathes of empirical evidence. Drawing on a combination of open-ended probing data, supervised machine learning, and a U.S. representative quota sample, our study compares the validity of standard

In this paper, we investigate the conditions under which data imbalances, a common data characteristic that occurs when factor values are unevenly distributed, are problematic for the performance of Coincidence Analysis (CNA). We further examine how such imbalances relate to fragmentation and noise in data. We show that even extreme data imbalances, when not combined with fragmentation or noise, do

Distances derived from word embeddings can measure a range of gradational relations—similarity, hierarchy, entailment, and stereotype—and can be used at the document- and author-level in ways that overcome some of the limitations of weighted dictionary methods. We provide a comprehensive introduction to using word embeddings for relation induction, and demonstrate how such techniques can complement

The promise of process tracing methods is that they can help us better understand how things work in real-world cases. Despite the many advances in the past two decades, we contend that existing accounts result in either under-socialised accounts in which the moves made by actors are studied while neglecting the social dimension of action, or over-socialised accounts that are so focused on social context

Processes that unfold over individuals’ life courses are often associated with inequalities later in life. The literature lacks methodological approaches to analyze inequalities in outcomes between groups, for example, between women and men, in a life-course-sensitive manner. We propose a combination of methods—of sequence analysis, which enables us to study the multidimensional complexity of life

Visual data have dramatically increased in quantity in the digital age, presenting new opportunities for social science research. However, the extensive time and labor costs to process and analyze ...

Background:On August 31, 2017, Ohio passed legislation that regulates how opioids can be prescribed postoperatively. Studies have shown that such legislation is successful in reducing the morphine ...

Dynamic cerebral autoregulation (dCA) is a key mechanism that regulates cerebral blood flow (CBF) in response to transient changes in blood pressure (BP). Impairment of dCA could increase vulnerabi...

We studied 30 healthy volunteers (60 arms), categorized into three age groups with equal numbers to verify if a 22 MHz compared with a 15 MHz ultrasound transducer has additional value for studying...

Asit Biswas and Shubh Brat Sarkar (Eds.), Dalit Poems, Songs and Dialogues from Bengal in English Translation (Kolkata: Ababil Books, 2019), 266 pp., ₹495, ISBN: 978-8-1939-3923-9 (Paperback).

Juned Shaikh, Outcaste Bombay: City Making and the Politics of the Poor. Orient BlackSwan Private Ltd, 2021, 227 pp., ₹995.

In the wake of the methodological developments that aim to render qualitative comparative analysis (QCA) “time sensitive”, I propose a new procedure for carrying out QCA longitudinally. More specif...

The rise of social media has opened countless opportunities to explore social science questions with new data and methods. However, research on socioeconomic inequality remains constrained by limit...

Multilevel models are often used to account for the hierarchical structure of social data and the inherent dependencies to produce estimates of regression coefficients, variance components associat...

In the United States and elsewhere, risk assessment algorithms are being used to help inform criminal justice decision-makers. A common intent is to forecast an offender’s “future dangerousness.” S...

The use of inter-rater reliability (IRR) methods may provide an opportunity to improve the transparency and consistency of qualitative case study data analysis in terms of the rigor of how codes an...

Video data analysis (VDA) represents an important methodological framework for contemporary research approaches to the myriad of footage available from cameras, devices, and phones. Footage from po...

Video data offer important insights into social processes because they enable direct observation of real-life social interaction. Though such data have become abundant and increasingly accessible, ...

Policy evaluation studies, which assess the effect of an intervention, face statistical challenges: in real-world settings treatments are not randomly assigned and the analysis might be complicated...

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular inf...

Discrete-time survival analysis (DTSA) models are a popular way of modeling events in the social sciences. However, the analysis of discrete-time survival data is challenged by missing data in one ...

Transformer-based models for transfer learning have the potential to achieve high prediction accuracies on text-based supervised learning tasks with relatively few training data instances. These mo...

Measuring meaning is a central problem in cultural sociology and word embeddings may offer powerful new tools to do so. But like any tool, they build on and exert theoretical assumptions. In this p...

Mixed-mode surveys are popular as they can save costs and maintain (or improve) response rates relative to single-mode surveys. Nevertheless, it is not yet clear how design decisions like survey mo...

Ethnographic and interview research have made significant contributions to cumulative social science and influenced the public conversation around important social issues. However, debates rage ove...

Increasingly, the broader public, media and policymakers are looking to qualitative research to provide answers to our most pressing social questions. While an exciting and perhaps overdue moment f...

The last decade witnessed a spectacular rise in the volume of available textual data. With this new abundance came the question of how to analyze it. In the social sciences, scholars mostly resorte...

Public culture is a powerful source of cognitive socialization; for example, media language is full of meanings about body weight. Yet it remains unclear how individuals process meanings in public ...

Radical-right campaigns commonly employ three discursive elements: anti-elite populism, exclusionary and declinist nationalism, and authoritarianism. Recent scholarship has explored whether these f...

As the field of computational text analysis within the social sciences is maturing, computational methods are no longer seen as ends in themselves, but rather as means toward answering theoreticall...

Taking a sociological view, we can investigate the empirical consequences of variations in the rhetoric of sociological methodology. The standards advocated in Qualitative Literacy divide communiti...

Small and Calarco have done the field a great service; we must go further and arm readers with better understandings of when authors have in fact fulfilled Small and Calarco’s strictures.

This article uses the interventionist theory of causation, a counterfactual theory taken from philosophy of science, to strengthen causal analysis in process tracing research. Causal claims from pr...

In social stratification research, the most frequently used social class schema are based on employment relations (EGP and ESEC). These schemes have been propelled to paradigms for research on soci...

This article presents a computational approach to examining immigrant incorporation through shifts in the social “mainstream.” Analyzing a historical corpus of American etiquette books, texts from ...

Research in organizational theory takes as a key premise the notion that organizations are “actors.” Organizational actorhood, or agency, depends, in part, on how external audiences perceive organi...

Egocentric networks represent a popular research design for network research. However, to what extent and under what conditions egocentric network centrality can serve as reasonable substitutes for...

The network scale-up method (NSUM) is a survey-based method for estimating the number of individuals in a hidden or hard-to-reach subgroup of a general population. In NSUM surveys, sampled individu...

This paper considers the adoption of computational techniques within research designs modeled after the extended case method. Echoing calls to augment the power of contemporary researchers through ...

Text as Data represents a major advance for teaching text analysis in the social sciences, digital humanities and data science by providing an integrated framework for how to conceptualize and depl...

In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactio...

Grouped and right-censored (GRC) counts have been used in a wide range of attitudinal and behavioural surveys yet they cannot be readily analyzed or assessed by conventional statistical models. Thi...

Missing data are a pervasive problem in data analysis. Three common methods for addressing the problem are (a) complete-case analysis, where only units that are complete on the variables in an anal...

A growing body of social science research investigates whether the economic payoff to a college education is heterogeneous — in particular, whether disadvantaged youth can benefit more from attendi...

The impact of a major historical event on child and youth development has been of great interest in the study of the life course. This study is focused on assessing the causal effect of the Great R...

Many students of statistics and econometrics express frustration with the way a problem known as “bad control” is treated in the traditional literature. The issue arises when the addition of a vari...

The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find solutions stemming from the former, with the latter being less

Adaptive survey design refers to using targeted procedures to recruit different sampled cases. This technique strives to reduce bias and variance of survey estimates by trying to recruit a larger and more balanced set of respondents. However, it is not well understood how adaptive design can improve data and survey estimates beyond the well-established post-survey adjustment. This paper reports the

Over the past decade, sociologists have become increasingly interested in the formal study of semantic relations within text. Most contemporary studies focus either on mapping concept co-occurrences or on measuring semantic associations via word embeddings. Although conducive to many research goals, these approaches share an important limitation: they abstract away what one can call the event structure

When the social boundaries between groups are breached, the tendency for people to erect and maintain symbolic boundaries intensifies. Drawing on extant perspectives on boundary maintenance, we distinguish between two strategies that people pursue in maintaining symbolic boundaries: boundary retention—entrenching themselves in pre-existing symbolic distinctions—and boundary reformation—innovating new

Social scientists increasingly use video data, but large-scale analysis of its content is often constrained by scarce manual coding resources. Upscaling may be possible with the application of automated coding procedures, which are being developed in the field of computer vision. Here, we introduce computer vision to social scientists, review the state-of-the-art in relevant subfields, and provide